Self-Serving Bias in Visitors' Perceptions of the Impacts of Tourism
Bibliographic record
Abstract
AbstractThis study explores tourism destination impacts through the unique lens of visitors' perceptions of their contributions to impacts. Self-serving bias of attributions was used as the theoretical framework to examine how campers in the Canadian Rocky Mountain National Parks perceived the impacts of their own behavior on the destination. In total 241 campers completed self-administered questionnaires that assessed common tourism impacts, camping experience, and socio-demographic characteristics. Results of factor analysis indicated three dimensions of impacts: immediate; gradual; and economic. Findings suggested that while visitors recognized their immediate and economic impacts on the destination, their contribution to gradual impacts depended upon an interaction between camping experiences and destination experience. The temporal nature of impacts, coupled with the interaction effect support self-serving bias as a useful framework to explain how visitors perceive their own impacts at a vacation destination. Implications for persuasive communication are discussed.KEYWORDS: Self-serving biastourism impactspast experience
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".